Negotiable
Undetermined
Remote
Remote or Hybrid
Summary: The role is for a Senior AI Engineer with a focus on Generative AI and Large Language Models (LLMs). Candidates are expected to have strong technical skills in AI solutions, particularly in architecting and delivering projects independently. The position is fully remote, requiring immediate qualified profiles capable of leading AI initiatives. The ideal candidate will have extensive experience with various AI technologies and frameworks.
Key Responsibilities:
- Architect and deliver AI solutions independently.
- Develop expertise in Generative AI and Large Language Models (LLMs).
- Implement Retrieval-Augmented Generation (RAG) techniques.
- Build AI Agents and Agentic AI solutions.
- Utilize Python for development tasks.
- Work with Azure AI Search and Semantic Kernel.
- Manage Vector Databases and embeddings.
- Orchestrate LLM frameworks such as Semantic Kernel, LangChain, and others.
- Engage in prompt engineering and context management.
- Deploy AI applications on Azure and develop APIs.
Key Skills:
- Strong experience with Generative AI and LLMs.
- Hands-on expertise in RAG.
- Proficient in Python development.
- Experience with Azure AI Search and Semantic Kernel.
- Understanding of Vector Databases and embeddings.
- Familiarity with LLM orchestration frameworks.
- Knowledge of prompt engineering and agent workflows.
- Experience with document ingestion and retrieval pipelines.
- API development and integration skills.
- Knowledge of Docker and Kubernetes is a plus.
Salary (Rate): undetermined
City: undetermined
Country: undetermined
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: Senior
Industry: IT
Required Skills
Strong experience with Generative AI and Large Language Models (LLMs)
Hands-on expertise in RAG (Retrieval-Augmented Generation)
Experience building AI Agents / Agentic AI solutions
Strong Python development skills
Experience with Azure AI Search
Experience with Semantic Kernel
Strong understanding of Vector Databases and embeddings
Experience with LLM orchestration frameworks such as:
Semantic Kernel
LangChain
LangGraph
CrewAI
AutoGen
Knowledge of prompt engineering, context management, memory, and agent workflows
Preferred Technical Experience
OpenAI, Azure OpenAI, Anthropic, Gemini, or similar LLM platforms
Vector databases such as:
Pinecone
Weaviate
Chroma
Qdrant
Azure AI Search Vector Index
Experience with document ingestion, chunking, embeddings, and retrieval pipelines
Experience deploying AI applications on Azure
API development and integration experience
Knowledge of Docker, Kubernetes, and cloud-native architectures is a plus
Experience Level
Senior-level resources
Able to independently architect and deliver AI solutions
Nice to Have
Experience building enterprise copilots and AI assistants
Multi-agent orchestration experience
Knowledge graph integration
Fine-tuning, evaluation frameworks, and AI observability
Experience with enterprise security, governance, and responsible AI practices
Need qualified profiles immediately. Candidates should be capable of leading AI initiatives from architecture through production deployment